Instructions to use Ammok/my_audio_model01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammok/my_audio_model01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Ammok/my_audio_model01")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Ammok/my_audio_model01") model = AutoModelForAudioClassification.from_pretrained("Ammok/my_audio_model01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fcf61551b3bd948ac742f622f4fbb41218dfe04159b657564b01038b6c0adec4
- Size of remote file:
- 378 MB
- SHA256:
- 96753041ddcd9986a42b28f82bf79af3c6fb320ece587102de472a2e207ed878
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